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Silver BlogA Complete Guide to Choosing the Best Machine Learning Course


A collection of the best courses covering machine learning concepts and techniques, including supervised and unsupervised learning, and hands-on modeling to develop algorithms and prepare you for the role of Machine Learning Engineer.



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By Simplilearn

Why Should You Choose Machine Learning as a Career?

With the machine learning market size expected to grow from $1.03 Billion USD in 2016 to $8.81 Billion USD by 2022, it can almost be said that machine learning is taking over the world. With that, there is a growing need for professionals who know the ins and out of machine learning.

According to Forbes, machine learning patents grew at a 34 percent Compound Annual Growth Rate (CAGR) between 2013 and 2017, which is the third-fastest growing category of all patents granted. Also, the International Data Corporation (IDC) forecasts that spending on AI and ML will increase from $12 Billion USD in 2017 to $57.6 Billion USD by 2021. Even Deloitte Global predicts that the number of machine learning pilots and implementations will double in 2018 compared to 2017, and double again by 2020.

Simplilearn Machine Learning

Keeping all these facts in mind, it is safe to say that machine learning as an industry is continuing to grow. Now is the time to get into machine learning by enrolling in a machine learning course that imparts you with the practical knowledge to make your future brighter.

Before getting into different ways to learn Machine Learning, have a look at the basics of ML, different types of ML and various application of ML.

Different Ways to Learn Machine Learning

  1. Online Machine Learning Course

One of the best ways to learn machine learning is by enrolling in an online education program or taking an online course. There are several online course providers in the market, and different modes of online study. You can opt for self-learning courses or virtual classroom courses, or those which blend the two. One of the main benefits of online learning is the flexibility it provides.You can learn at any hour of the day and when it is most convenient for you, unlike traditional classroom learning. Also, online learning can save you a lot of time, since you won’t have to travel to a physical location to attend classes. You do, however, need a good, stable internet connection. Depending on the specific program you enroll in, you may also need to be comfortable with interacting with others online over video or chat sessions.

  1. College Course/ College Degree

Learning at a university offers you in-person interaction with professors, but you won’t get the same flexibility in schedule that you would with online courses. Additionally, university degree courses are often not optimal when it comes to developing practical skills. This is because the focus is a lot more on the academic foundations, rather than interacting and working with industry professionals. And when it comes to enrolling in a college course, it usually means pursuing a two or four-year degree.

These days, succeeding in the technology industry doesn’t necessarily require this amount of higher education. Attending a technical school or receiving online certification is often more than sufficient. In fact, many industry professionals tend to agree that shorter, more condensed learning is actually better, because you are focusing solely on what you want to learn. This also means you finish your program much faster.

  1. Learn Machine Learning Through Self-Study / On-the-Job

Anyone who has a basic understanding of machine learning can sharpen their skills through online blogs and materials. There are also some great resources on YouTube, like this Machine Learning Playlist by Simplilearn, which provides excellent foundation level videos on machine learning. But the biggest drawback of learning through self-study is that it will take a lot longer to learn the basics, and you might end up making avoidable, but very costly mistakes. You also don’t get the opportunity  to learn from and interact with industry professionals. You may find it difficult to manage your time when it comes to self-study as well.

Benefits of Learning ML through an Online Course

  1. It’s Career-Focused

A professional machine learning course is great when you are looking to achieve specific career goals in a short period of time. Focused courses geared toward various projects can teach you how you can apply machine learning in real life. Projects like building a predictive model for housing prices, building a phishing website detector using LR algorithms or KNN algorithms, or building an MNIST Classifier provides curated content for professionals to upskill in those specific areas versus a broad education. University degrees also have a much longer, undefined return on investment, as they are not always geared towards specific goals.

  1. It Saves Time

A machine learning certification course will generally take between one to six months to complete, depending on your goals. A degree from a university, on the other hand, can take up to four years or more. If you are looking to further your education with a professional degree, you are looking at more time on top of that. It’s questionable whether all these years in school are necessary when pursuing a career in machine learning, as a good certification course can often offer you all the skills you need to succeed.

  1. It Saves on Cost

Machine learning certifications don’t cost as much as university degrees for several reasons:

    1. The certification courses are of lesser duration, so naturally, any operational costs are lower
    2. Most renowned machine learning certification courses, like Simplilearn’s Machine Learning Certification Course, are entirely online, so there are no operational overhead costs. Students also don’t have to worry about transportation and living expenses when it comes to getting to class. Earning a university degree, on the other hand, often requires on-campus visits, which can add to the overall education cost.
  1. It’s Flexible

One huge advantage of receiving a machine learning certification is that most courses are available online, and you can study from anywhere if you have a good internet connection. Whether you’re at home, commuting to or from work, or are on vacation, online learning affords you the flexibility to learn anywhere, and on any device.

  1. Training is Highly Engaging

All renowned online certification providers rely on student feedback to determine which instructors are good and which aren’t. They use this constructive feedback as they design future education programs. Experienced and knowledgeable professors with years of experience at the university may still not offer the practical learning experience you’re looking for, or the personalized attention you’re seeking.

  1. Individualized Learning

Online learning can help students harness their strengths and minimize weaknesses by focusing on various projects, labs and guided assistance through well-known teaching assistants, such as the ones that are provided in Simplilearn’s courses.

Good Online Machine Learning Courses

  1. Simplilearn’s Machine Learning Certification Course

Simplilearn’s Machine Learning Certification Course provides practical learning on machine learning concepts and techniques, including supervised and unsupervised learning, mathematical and heuristic aspects, and hands-on modeling to develop algorithms and prepare you for the role of Machine Learning Engineer.

A machine learning expert conducts sessions via live, online classes. Students also receive lifetime access to the self-paced learning modules. You can practice what you learn through four real-life industry projects. The education program also offers dedicated mentoring sessions from faculty who are also industry experts.

  1. Coursera’s Machine Learning Course

This course is also a popular choice. It has various concepts and in-depth knowledge on machine learning to offer students. However, you might have to compromise on hands-on exercises.You will likely find this course flexible and can schedule the classes according to your convenience, but students may not receive lifetime access to the study materials and instructors’ support.

  1. edX’s Machine Learning Course

Columbia University offers this course through edX. You might find it more authoritative, but again, you might have to face the flexibility issues in terms of scheduling your classes as you’ll be bounded by the university’s rules. Also, you might not be able to interact with your instructor frequently, and you may be required to learn more academic concepts, rather than work on practical real-world projects.

There are many other providers of online machine learning courses, but the above are some of the most popular options. You can choose any of them according to your requirements and based on the selections they provide.


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